The current refugial rainforests of Sundaland are unrepresentative of their biogeographic past and highly vulnerable to disturbance
Bibliographic record
Abstract
Understanding the historical dynamics of forest communities is a critical element for accurate prediction of their response to future change. Here, we examine evergreen rainforest distribution in the Sunda Shelf region at the last glacial maximum (LGM), using a spatially explicit model incorporating geographic, paleoclimatic, and geologic evidence. Results indicate that at the LGM, Sundaland rainforests covered a substantially larger area than currently present. Extrapolation of the model over the past million years demonstrates that the current "island archipelago" setting in Sundaland is extremely unusual given the majority of its history and the dramatic biogeographic transitions caused by global deglaciation were rapid and brief. Compared with dominant glacial conditions, lowland forests were probably reduced from approximately 1.3 to 0.8 x 10(6) km(2) while upland forests were probably reduced by half, from approximately 2.0 to 1.0 x 10(5) km(2). Coastal mangrove and swamp forests experienced the most dramatic change during deglaciations, going through a complete and major biogeographic relocation. The Sundaland forest dynamics of fragmentation and contraction and subsequent expansion, driven by glacial cycles, occur in the opposite phase as those in the northern hemisphere and equatorial Africa, indicating that Sundaland evergreen rainforest communities are currently in a refugial stage. Widespread human-mediated reduction and conversion of these forests in their refugial stage, when most species are passing through significant population bottlenecks, strongly emphasizes the urgency of conservation and management efforts. Further research into the natural process of fragmentation and contraction during deglaciation is necessary to understand the long-term effect of human activity on forest species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".